Full-Stack Engineer

End-to-End SaaS Platforms & Web Applications

I ship complete production SaaS platforms — from responsive Next.js frontends to scalable Node.js/Python backends with auth, payments, and real-time data.

Next.jsReactNode.jsPythonSaaS

Technical Skills

What I bring as a Full-Stack engineer

Frontend

Next.js 15/16— App Router, SSR & Server Components
React 19— Modern hooks & concurrent features
TypeScript— Strict type safety across the stack
Tailwind CSS— Responsive design systems

Backend

Node.js / NestJS— Scalable API servers
Python / FastAPI— AI-powered backend services
PostgreSQL / Prisma— Type-safe relational data
MongoDB / Mongoose— Document & geospatial data

Product Features

Auth (JWT / OAuth)— Secure role-based access
Payments— LemonSqueezy & Stripe integration
Real-Time— WebSockets, SSE & live updates
File Upload / S3— Cloud asset management

DevOps & Shipping

Docker— Containerized deployments
Nginx / PM2— Production process management
GitHub Actions— Automated CI/CD pipelines
Vercel / VPS— Flexible hosting strategies

Architecture

How I architect full-stack systems

01

Product Architecture

Define user flows, feature requirements, database schema, and API contracts before development begins.

02

Frontend Foundation

Next.js App Router with Server Components for performance, responsive Tailwind layouts, and accessible UI components.

03

Backend & Data

RESTful APIs with NestJS or Express, PostgreSQL/MongoDB schemas, auth middleware, and payment webhook handling.

04

Integration & Polish

Connect frontend to API, add real-time features, optimize Core Web Vitals, and implement error boundaries.

05

Deploy & Scale

Containerized deployment, CDN configuration, monitoring, and performance optimization for production traffic.

Featured Work

Production projects as a Full-Stack engineer

AI SaaS PlatformLive in Production

Planfluence

Meetings into Momentum — AI Meeting Intelligence to Jira Backlog & Slack Recaps

Problem

Engineering discussions frequently end with action items and architectural commitments buried in unreviewed recordings or chat threads. Translating spoken consensus into Jira tickets with acceptance criteria wastes hours of developer and manager time.

Solution

Architected a 4-step pipeline: (1) Capture calls via Google Meet Chrome extension without intrusive bots; (2) Transcribe and extract decisions using Whisper and LLMs; (3) Review, approve, and publish tickets directly to Jira Cloud/Data Center and Trello backlogs; (4) Broadcast structured recaps to dedicated project Slack channels.

Architecture

  • Chrome Extension (Manifest V3) capturing tab audio locally with zero bots joining user meetings
  • Next.js 15 App Router web application with streaming AI summaries and interactive decision editor
  • High-speed Whisper transcription & structured JSON extraction for action items and acceptance criteria
  • Bi-directional Jira Cloud & Trello API integrations with one-click backlog and sprint publishing
  • Slack webhook automation broadcasting project-specific meeting recaps with deep links
  • Lemon Squeezy merchant-of-record subscription billing engine

Verified Results

Zero-bot audio capture eliminating attendee distraction and call overheadReduced post-meeting Jira ticket creation time from ~45 minutes to < 60 secondsSeamless bi-directional synchronization across Google Meet, Jira, Trello, and Slack
Next.js 15TypeScriptChrome ExtensionOpenAI Whisper & GPT-4oAtlassian Jira APISlack APILemon SqueezyTailwind CSS
View Live
Local-First MobileLive in Production

GeniSteps

Hardware-Accurate Step Tracking & Vitality Companion — 100% Local-First

Problem

Mainstream pedometers drain device battery, lock essential 24-hour trends and data exports behind $39–$79/yr recurring subscriptions, and harvest sensitive biometric location and movement data to proprietary cloud servers.

Solution

Built a silicon-native motion engine with a 4th-order DSP bandpass filter (0.8–3.5 Hz) tuned to human gait biomechanics. Features silent lock-screen updates via >95% IPC throttling, natural stride pacing (~320ms), and 100% data sovereignty in on-device SQLite WAL mode.

Architecture

  • Silicon coprocessor integration: Apple CoreMotion (CMMotionActivityManager) & Android Sensor Hub
  • 4th-Order DSP digital signal processing filter (0.8–3.5 Hz) isolating true strides from vehicle vibration
  • Silent lock-screen live activity widgets with >95% IPC throttling for battery preservation
  • Local-first SQLite database running in WAL mode with instant 1-tap CSV and JSON spreadsheet export
  • Behavioral habit psychology engine: automated bankable streak freezes and rest-day scheduling
  • Standardized machine-readable /llms.txt factsheet for generative engine and AI model evaluation

Verified Results

< 1% daily battery overhead utilizing dedicated hardware coprocessors100% private: zero cloud servers, zero account creation, zero analytics tracking$0 forever: complete professional feature set with zero subscriptions or paywalls
React NativeApple CoreMotionAndroid Sensor HubSQLite (WAL)TypeScriptDSP FiltersiOS Live Activities
View Live
B2B MarketplaceLive in Production

DispatchLink

B2B Freight Marketplace Connecting Carriers & Dispatchers

Problem

Freight dispatching is plagued by manual phone calls, untracked load confirmations, fragmented broker commissions, and slow escrow reconciliation.

Solution

Architected a unified real-time portal where carriers claim loads with automated geospatial radius search, live driver telemetry, and automated multi-tenant wallet payouts.

Architecture

  • Next.js 15 App Router with Server Components for low-latency freight searches
  • MongoDB 2dsphere indexes for polygon and radius origin-to-destination matching
  • MapLibre vector maps rendering live driver routes and telemetry coordinates
  • LemonSqueezy merchant-of-record integration for multi-party escrow billing

Verified Results

1,048+ matched freight dispatches processedReduced load confirmation turnaround by ~42% compared to manual brokersZero-drop webhook processing for payment and dispatch milestones
Next.js 15MongoDB GeospatialMapLibreLemonSqueezyTypeScriptTailwind CSS
View Live
Gen AI & VoiceLive in Production

Kookabe AI Suite

Enterprise WhatsApp RAG Chatbot & Automated AI Voice Mail

Problem

Companies received hundreds of repetitive WhatsApp voice notes, PDFs, and product inquiries daily, resulting in 4-8 hour response delays and missed sales leads.

Solution

Built a hybrid RAG system with pgvector and Claude 3.7 that parses customer inquiries, searches internal PDF documentation, and generates accurate answers with human-handoff triggers.

Architecture

  • WhatsApp Business API webhooks ingesting incoming text, voice notes, and document files
  • Hybrid RAG combining pgvector dense embeddings with BM25 keyword reranking
  • FastAPI backend handling asynchronous LLM streaming and conversation state
  • Automated audio transcription pipeline extracting lead data directly into CRM webhooks

Verified Results

Automated over 90% of routine inquiries with sub-3-second first responsesZero hallucinations verified via strict citation and source-chunk verificationContinuous 24/7 uptime handling high-volume customer messages
LangChainClaude 3.7FastAPIPostgreSQL / pgvectorWhatsApp Cloud APIRedis
View Live

Experience

Where I've applied these skills

Founder & Lead Architect

atThe Geni SolutionsStudio & Products

2024 — Present

Founded and lead The Geni Solutions, an elite AI & software studio engineering autonomous LangGraph multi-agent workflows, enterprise RAG engines, and high-performance SaaS and mobile products.

  • Architected and shipped Planfluence (planfluence.site), an automated meeting-to-backlog platform with Google Meet Chrome extension capture, Whisper transcription, Jira/Trello automation, and Slack recaps.
  • Engineered GeniSteps (genisteps.thegenisolutions.com), a 100% local-first iOS & Android vitality companion leveraging silicon CoreMotion/sensor hubs, 4th-order DSP filters, and private SQLite WAL storage.
  • Standardized an agile 4-phase AI delivery process (Strategy & Mapping → Benchmark POC → Full Engineering → Guardrailed Deployment) delivering <200ms agent SLA and 99.4% retrieval accuracy.
  • Spearheaded multi-agent orchestrations, enterprise WhatsApp AI bots, and custom SaaS platforms across North America and global clients.
LangGraphLangChainNext.js 15PythonFastAPIPostgreSQL / pgvectorLocal-First SQLiteChrome ExtensionsDocker

AI & Full-Stack Engineer

atUpworkTop Rated

May 2026 — Present

Delivering production AI workflows, full-stack Next.js/NestJS platforms, and cloud DevOps systems for high-growth tech startups and international clients.

  • Consulting on AI agent architecture, hybrid RAG pipelines, and conversational voice systems.
  • Building scalable REST APIs, microservices, and database schemas with PostgreSQL and Prisma.
  • Maintaining a 100% Job Success Score with verified 5-star client contracts.
AI AgentsLangChainClaude 3.7Next.jsNestJSPostgreSQLDocker

Software Engineer

atDev House

May 2024 — Sep 2026

Engineered distributed message queues, asynchronous background worker pipelines, and backend microservice modules for enterprise clients.

  • Collaborated on Node.js and TypeScript microservice integrations with BullMQ queues.
  • Engineered decoupled background workers and Redis caching layers for high-throughput workloads.
  • Built modular REST API endpoints and optimized database query execution.
Node.jsTypeScriptBullMQRedisDockerREST APIs

Process

How I work

01

Discovery & Planning

Understand the business problem, map user flows, and define the MVP scope.

02

Rapid Prototyping

Ship a working prototype with core features to validate assumptions early.

03

Full Development

Build out the complete product with auth, payments, real-time features, and polish.

04

Launch & Iterate

Deploy, monitor production metrics, and iterate based on real user feedback.

FAQ

Frequently asked questions

Do you build entire SaaS products from scratch?

Yes. I've founded The Geni Solutions and shipped production platforms like Planfluence (AI meeting-to-backlog SaaS) and GeniSteps (local-first mobile companion) from database design to deployment. I own the complete vertical — frontend, backend, auth, payments, DevOps.

What's your frontend tech stack?

Next.js 15/16 with App Router and Server Components, React 19, TypeScript, and Tailwind CSS. I build responsive, accessible interfaces with strong Core Web Vitals performance.

Can you work on an existing codebase?

Absolutely. I audit existing code, identify performance bottlenecks, refactor architecture where needed, and add new features without breaking existing functionality.

Do you handle payments and auth?

Yes — I integrate LemonSqueezy and Stripe for payment processing, webhooks, and multi-party escrow. For auth, I implement JWT, OAuth, and role-based access control.

Need a complete SaaS platform built?

From UI to API to deployment — I own the entire stack and ship production products.